Monitoring equipment is used in all sorts of environments in society. In its simplest form, a video stream of a scene is observed by personnel and alerts are subsequently raised manually. By automating the monitoring, a more cost-effective and robust monitoring system may be achieved. Often, most features of interest in a monitoring system are related to motion in the scene. In general, reliable and robust automatic motion detection is difficult to achieve.
A simple algorithm for motion detection is to compare a current image with a reference image and simply register the changes in pixel intensity levels. However, this simple algorithm may be prone to trigger false alarms due to changes related to irrelevant motion, such as swaying trees or waves on puddles. False alarms may, in turn, result in increased costs related to the response.
In order to reduce the number of false alarms different filters may be used. Some examples of filters are small object filtering and swaying object filtering. Implementation of such filter may be complex and even after using them the number of false alarms may be too high.